Interactive Robotics Laboratory
Led by Ben Amor at Arizona State University, this lab develops novel machine learning techniques enabling robots to physically interact with objects and humans. Research uses reinforcement learning and policy search methods for manipulation tasks.
Notable work
Recent publications
All papers →Matched by this lab's specialties (keyword overlap + direct affiliation)
A fusion prediction model of tool wear based on physical information and machine learning in five-axis milling TC4 titanium alloy
Shaoqing Qin, Lida Zhu, Yanpeng Hao +7 more
Robotics and Computer-Integrated Manufacturing · 2026
Beyond rigid automation: A review of vision-language-action models for adaptive human–robot disassembly
Baki Ul Islam, Joao Paulo Jacomini Prioli, Jose Carlos Hernandez Azucena
Robotics and Computer-Integrated Manufacturing · 2027
Generalized machine learning model for deformation prediction and compensation in robotic machining
Taehwa Hong, Gyuho Kim, Seong Hyeon Kim +1 more
Robotics and Computer-Integrated Manufacturing · 2026
A hierarchical approach to imitation learning for manipulation tasks requiring time varying forces
Rishabh Shukla, Adithya Santhosh, Shaili Gandhi +2 more
Robotics and Computer-Integrated Manufacturing · 2026
Copilot: A framework for integrating LLM and BMI to enhance human–robot interaction
Siyu Liu, Mengzhen Liu, Zhiyuan Ming +6 more
Robotics and Computer-Integrated Manufacturing · 2026
A machine learning–based tool for enhancing position accuracy in industrial robots with a reduced dataset
Giuseppe Romano, Pietro Bilancia, Alberto Locatelli +3 more
Robotics and Computer-Integrated Manufacturing · 2026